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Source channel @githubtrending · Post #14926 · Jul 8

#jupyter_notebook#artificial_intelligence#book#large_language_models#llm#llms#oreilly#oreilly_books You can learn how to use Large Language Models (LLMs) effectively through the book *Hands-On Large Language Models* by Jay Alammar and Maarten Grootendorst. This book uses nearly 300 custom illustrations to explain key concepts and practical tools for working with LLMs, including tokenization, transformers, prompt engineering, fine-tuning, and advanced text generation. It also provides runnable code examples in Google Colab, making it easy to practice and apply what you learn. This resource helps you understand and build your own LLM applications confidently, saving you time and effort in mastering complex AI technology. It’s highly recommended for anyone wanting hands-on experience with LLMs. https://github.com/HandsOnLLM/Hands-On-Large-Language-Models

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@emagzinewspars · Post #9561 · 11/17/2025, 03:17 AM

#The_Science🇺🇸📕[PDF]⬇️ 13 #November2025 #Weekly_Magazines For learning, for free(dom). @backupofmagazines This issue dives into breakthroughs reshaping biology and energy as researchers confront rising geopolitical limits. From #AI-driven epigenetics to #SyntheticBiology advances, the issue tracks how innovation pushes ahead despite tensions over China-US research ties. New micro-robots navigating the bloodstream and faster-charging batteries highlight a surge in #DeepTech momentum. Climate resilience, #PandemicPreparedness, and EU chemical reforms underscore global policy stakes. Studies on dog domestication, brown dwarfs, and marine recovery after extinction broaden the scientific lens. A reminder that #ScienceMatters even as politics shift—innovation continues to define our shared future. #TechNews#GlobalTrends#ResearchUpdates